In recent years, attention has been focused on technologies of inputting speech of words uttered by humans and executing functions corresponding to recognition results of the input speech. These technologies are used as a speech interface of devices such as mobile phones and car navigations. As a basic algorithm, assumed speech recognition results and functions are associated in advance, and in a case where a recognition result of input speech has been assumed, a function corresponding to this recognition result is executed. Since a function is directly executed by utterance of a user in this manner, this is effective as a shortcut for designating a function to be executed.
Meanwhile, in order for a user to execute an intended function, it is necessary to utter a term corresponding to the function. Therefore, as the number of functions executable in a system increase, the number of terms the user has to memorize also increases. In this case, if the user does not sufficiently understand an operation manual of the system, there is a possibility that the user does not know which term should be uttered when executing the intended function.
As a conventional technique for solving such problems, there is a device described in Patent Literature 1, for example. In this device, the number of times of timeouts of speech input designating a function to be executed or the number of times of correction of this speech input is counted, and the comprehension level of a user with respect to the content of a guidance sentence encouraging designation of the function is estimated from the counting result. Then, from among guidance sentences having different degree of details of the content, a guidance sentence having a degree of details corresponding to the estimated comprehension level is presented to the user.
In addition, in a method described in Patent Literature 2, for example, feature words are extracted for each category from tag information of a user's social bookmark. Then, on the basis of history or other information of Web pages, the frequency at which a feature word is used in the Web pages accessed by the user is counted, and a category in which the usage frequency of the feature word is less than or equal to a threshold value is determined as a category unknown to the user. In the case where a feature word of a Web page browsed by the user belongs to the unknown category, it is determined that the feature word of this Web page is the user's unknown word, and an explanatory sentence of the unknown word is presented to the user.